Department of Gynecology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Institute of Cancer and Basic Medicine, Zhejiang Cancer Hospital, Hangzhou, China.
Yonsei Med J. 2023 Mar;64(3):197-203. doi: 10.3349/ymj.2022.0239.
This study aimed to identify the risk factors and sonographic variables that could be integrated into a predictive model for endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) in women with abnormal uterine bleeding (AUB).
This retrospective study included 1837 patients who presented with AUB and underwent endometrial sampling. Multivariable logistic regression was developed based on clinical and sonographic covariates [endometrial thickness (ET), resistance index (RI) of the endometrial vasculature] assessed for their association with EC/AEH in the development group (n=1369), and a predictive nomogram was proposed. The model was validated in 468 patients.
Histological examination revealed 167 patients (12.2%) with EC or AEH in the development group. Using multivariable logistic regression, the following variables were incorporated in the prediction of endometrial malignancy: metabolic diseases [odds ratio (OR)=7.764, 95% confidence intervals (CI) 5.042-11.955], family history (OR=3.555, 95% CI 1.055-11.971), age ≥40 years (OR=3.195, 95% CI 1.878-5.435), RI ≤0.5 (OR=8.733, 95% CI 4.311-17.692), and ET ≥10 mm (OR=8.479, 95% CI 5.440-13.216). A nomogram was created using these five variables with an area under the curve of 0.837 (95% CI 0.800-0.874). The calibration curve showed good agreement between the observed and predicted occurrences. For the validation group, the model provided acceptable discrimination and calibration.
The proposed nomogram model showed moderate prediction accuracy in the differentiation between benign and malignant endometrial lesions among women with AUB.
本研究旨在确定风险因素和超声变量,以便纳入预测模型,用于预测患有异常子宫出血(AUB)的女性的子宫内膜癌(EC)和非典型子宫内膜增生(AEH)。
本回顾性研究纳入了 1837 名因 AUB 就诊并接受子宫内膜取样的患者。在发展组(n=1369)中,基于临床和超声协变量(子宫内膜厚度[ET]、子宫内膜血管的阻力指数[RI])进行多变量逻辑回归,以评估其与 EC/AEH 的相关性,并提出预测列线图。在 468 名患者中验证了该模型。
组织学检查显示,发展组中有 167 名患者(12.2%)患有 EC 或 AEH。使用多变量逻辑回归,将以下变量纳入子宫内膜恶性肿瘤的预测:代谢性疾病(比值比[OR]=7.764,95%置信区间[CI]5.042-11.955)、家族史(OR=3.555,95%CI 1.055-11.971)、年龄≥40 岁(OR=3.195,95%CI 1.878-5.435)、RI≤0.5(OR=8.733,95%CI 4.311-17.692)和 ET≥10mm(OR=8.479,95%CI 5.440-13.216)。使用这五个变量创建了一个列线图,曲线下面积为 0.837(95%CI 0.800-0.874)。校准曲线显示观察到的和预测的发生率之间有良好的一致性。对于验证组,该模型提供了可接受的区分度和校准度。
该研究提出的列线图模型在区分 AUB 女性良性和恶性子宫内膜病变方面具有中等预测准确性。